DECISION MAKING, HABITUAL DOMAINS AND INFORMATION TECHNOLOGY

2002 ◽  
Vol 01 (01) ◽  
pp. 5-26 ◽  
Author(s):  
P. L. YU ◽  
C. I. CHIANG
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Human Behavior ◽  
Decision Problems ◽  
Habitual Domains ◽  
Competence Set Analysis ◽  
Decision Elements

In this paper, we discuss how information technology (IT) affects and influences people to make decisions. We first introduce human behavior mechanism and habitual domains — the software that drive the behaviors. Then we discuss the impacts of IT on decision elements and environment, and then IT's impacts on a variety of decision problems including routine problems, mixed routine problems, fuzzy problems and challenging problems. IT is useful in solving routine problems but not as obvious in solving fuzzy and challenging problems. To solve fuzzy and challenging problems, an effective concept and model of competence set analysis is introduced. Finally, we describe three types of competence set analysis and show how IT can help in these three types of problems.

EMPOWER MCDM BY HABITUAL DOMAINS TO SOLVE CHALLENGING PROBLEMS IN CHANGEABLE SPACES

2012 ◽  
Vol 11 (02) ◽  
pp. 457-490 ◽  
Author(s):  
YEN-CHU CHEN ◽  
HUNG-SHUN HUANG ◽  
PO-LUNG YU
Keyword(s):  
Human Behavior ◽  
Domain Theory ◽  
Decision Problems ◽  
Habitual Domains ◽  
Innovation Dynamics ◽  
Competence Set Analysis ◽  
Complex Decision ◽  
Hidden Parameters ◽  
The Way ◽  
Changing World

Challenging decision problems in changeable spaces are characterized by existence of complex decision parameters that are changing with time and situations, including criteria and alternatives. Some of these parameters may be critical for their effective solutions, but hidden in the depth of potential domains. In this rapidly changing world, including technology and attitude, without paying attention to the problems in changeable spaces, we could easily commit serious mistakes due to decision blinds, decision traps and/or decision shocks. The article starts with a brief description of the evolution of MCDM toward challenging problems in changeable spaces. Then it briefly sketches a dynamic human behavior mechanism and habitual domain theory which provide an effective list for us to search relevant decision parameters and pave the way for latter discussion. Competence set analysis, derived from habitual domain, is then introduced to exemplify decision blinds, decision traps and decision shocks in challenging decision problems. Checking lists and methods for discovering blinds and traps and for dealing with shocks are also provided. Innovation dynamics, a systematic network of thoughts, is introduced to further look out relevant key parameters in dynamic challenging problems. The related academic subjects in each link of the innovation dynamics are also explained, which allow us to see the complexity and interconnectivities among different challenging problems in changeable spaces. Finally we introduce three habitual domain tool boxes to empower ourselves to expand and enrich our thoughts into the depth of the potential domains of the challenging problems, which allows us to more effectively identify hidden parameters, problems and competence sets to reduce decision blinds, avoid decision traps and solve the problems, or dissolve the problems before they occur.

Information technology support for integrated supply chain modeling

2008 ◽  
Vol 27 (1) ◽  
pp. 3-13
Author(s):  
Charu Chandra ◽  
Jānis Grabis
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Supply Chain ◽  
Process Modeling ◽  
Service Oriented Architecture ◽  
Model Development ◽  
Integrated Models ◽  
Supply Chain Modeling ◽  
Decision Making Models ◽  
Integrated Supply Chain

Multiple interrelated decision-making models are frequently used in supply chain modeling. Model integration is a precondition for efficient development and utilization of these models. This paper discusses use of modern information technology (IT) techniques and methods for integration of supply chain decision-making models. The overall approach to using IT at various stages of model development is presented. Data and process modeling techniques are used to developed semi-formalized representation of integrated models. These models support integration of decision-making components with other parts of supply chain information system. Process modeling is also used to describe interrelationships among multiple decision-making models. This representation is used as the basis for implementation of integrated models. The service-oriented architecture is proposed as an implementation platform. The presented discussion serves as the basis for further developments in developing integrated supply chain decision-making models.

Neuroscience: The New English Major?

2021 ◽  
pp. 107385842110039
Author(s):  
Kristin F. Phillips ◽  
Harald Sontheimer
Keyword(s):  
Decision Making ◽  
Graduate Education ◽  
Human Behavior ◽  
Undergraduate Curriculum ◽  
Virginia Tech ◽  
Bachelor's Degree ◽  
State University ◽  
Human Interactions ◽  
English Major ◽  
The Brain

Once strictly the domain of medical and graduate education, neuroscience has made its way into the undergraduate curriculum with over 230 colleges and universities now offering a bachelor’s degree in neuroscience. The disciplinary focus on the brain teaches students to apply science to the understanding of human behavior, human interactions, sensation, emotions, and decision making. In this article, we encourage new and existing undergraduate neuroscience programs to envision neuroscience as a broad discipline with the potential to develop competencies suitable for a variety of careers that reach well beyond research and medicine. This article describes our philosophy and illustrates a broad-based undergraduate degree in neuroscience implemented at a major state university, Virginia Tech. We highlight the fact that the research-centered Experimental Neuroscience major is least popular of our four distinct majors, which underscores our philosophy that undergraduate neuroscience can cater to a different audience than traditionally thought.

scholarly journals Integrating multiple fuzzy expert systems under restricting requirements 

2012 ◽  
Vol 52 (No. 4) ◽  
pp. 187-196
Author(s):  
S. Aly ◽  
I. Vrana
Keyword(s):  
Decision Making ◽  
Expert Systems ◽  
Business Processes ◽  
New Product ◽  
Decision Problems ◽  
Food Chains ◽  
Problem Context ◽  
Multiple Factors ◽  
Decision Consistency ◽  
Fuzzy Expert Systems

The multiple, different and specific expertises are often needed in making YES-or-NO (YES/NO) decisions for treating a variety of business, economic, and agricultural decision problems. This is due to the nature of such problems in which decisions are influenced by multiple factors, and accordingly multiple corresponding expertises are required. Fuzzy expert systems (FESs) are widely used to model expertise due to its capability to model real world values which are not always exact, but frequently vague, or uncertain. In addition, they are able to incorporate qualitative factors. The problem of integrating multiple fuzzy expert systems involves several independent and autonomous fuzzy expert systems arranged synergistically to suit a varying problem context. Every expert system participates in judging the problem based on a predefined match between problem context and the required specific expertises. In this research, multiple FESs are integrated through combining their crisp numerical outputs, which reflect the degree of bias to the Yes/No subjective answers. The reasons for independency can be related to maintainability, decision responsibility, analyzability, knowledge cohesion and modularity, context flexibility, sensitivity of aggregate knowledge, decision consistency, etc. This article presents simple algorithms to integrate multiple parallel FES under specific requirements: preserving the extreme crisp output values, providing for null or non-participating expertises, and considering decision-related expert systems, which are true requirements of a currently held project. The presented results provides a theoretical framework, which can bring advantage to decision making is many disciplines, as e.g. new product launching decision, food quality tracking, monitoring of suspicious deviation of the business processes from the standard performance, tax and customs declaration issues, control and logistic of food chains/networks, etc. 

Rank Reversal and the VIKOR Method: An Empirical Evaluation

2018 ◽  
Vol 17 (02) ◽  
pp. 513-525 ◽  
Author(s):  
Blanca Ceballos ◽  
David A. Pelta ◽  
María T. Lamata
Keyword(s):  
Decision Making ◽  
Empirical Evaluation ◽  
Decision Problems ◽  
Multi Criteria Decision Making ◽  
Common Phenomenon ◽  
Vikor Method ◽  
Rank Reversal

Rank reversal is a common phenomenon in multi-criteria decision-making methods. It appears when the addition/deletion of new options to the alternatives’ set produces a change in the original ranking. In this contribution, we want to assess this phenomenon in the context of the VIKOR method. Using randomly generated multi-criteria decision problems, we confirmed that rank reversal existed and strongly depended on VIKOR’s parameter. Also, we observed that the influence of the number of alternatives was stronger than that of the number of criteria. Finally, although rank reversal may exist, we saw that it may not affect the top alternative of the ranking, thus potentially having a low impact.

Method for Selecting Storage Enterprises Based on IFHA

2015 ◽  
Vol 713-715 ◽  
pp. 1769-1772
Author(s):  
Jie Wu ◽  
Lei Na Zheng ◽  
Tie Jun Pan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Problems ◽  
Decision Making Process ◽  
Final Decision ◽  
Multiple Decision Makers ◽  
Intuitionistic Fuzzy ◽  
Averaging Operator

In order to reflect the decision-making more scientific and democratic, modern decision problems often require the participation of multiple decision makers. In group decision making process,require the use of intuitionistic fuzzy hybrid averaging operator (IFHA) to get the final decision result.

Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chang Liu ◽  
Pratibha Rani ◽  
Khushboo Pachori
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Circular Economy ◽  
Supplier Selection ◽  
Manufacturing Sector ◽  
Uncertain Information ◽  
Manufacturing Companies ◽  
Content Type ◽  
Sustainable Supplier Selection ◽  
Selection Of

PurposeDue to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.Design/methodology/approachThis paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.FindingsThe outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.Originality/valueSelecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.

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